Western Digital uses SAS® Asset Performance Analytics to identify potential failures early in the production process and subsequently avoid yield excursions

Western Digital is one of the world’s largest hard disk drive suppliers and a pioneer in hard disk drive storage manufacturing. The company’s ability to succeed despite competition from new players can in part be attributed to its commitment to quality. Quality improvements are driven by complete product and component traceability on the entire life cycle of every unit of hard disk drive manufactured, from suppliers to manufacturing, to testing, shipment and customer use. With SAS Asset Performance Analytics, Western Digital is able to predict yield excursions and reduce losses caused by the production of defective devices.

With a built-in case management system, the solution gives Western Digital engineers the insights they need to identify possible failures early in the production process and make timely decisions to avoid a yield excursion, ensuring Western Digital hard drives are of the highest quality.

KH Sim
Director of Hard Disk Drive Analytics

A proactive approach with big data analytics

To maintain its competitive edge, Western Digital must ensure volume and efficiency in the manufacturing and distribution of its hard disk drives. The Western Digital subsidiary that SAS partnered with produces millions of hard disk drives per year – and while the success rate is maintained at such high levels, the failure rate of even a fraction of a percentage results in the production of a million defective drives. Therefore minimizing customer losses is critical to its operations, and the company’s priority has been minimizing the distribution of such defective units.

While the Hard Disk Drive (HDD) Analytics department had been using software to perform root-cause analysis of yield excursion for several years, KH Sim, Director of HDD Analytics at Western Digital, wanted to move from a reactive approach to a predictive approach. Western Digital also needed a solution able to handle the increasing amount of data its systems were producing.

Western Digital had built a comprehensive data mart with thousands of variables comprising data from various manufacturing and supply chain processes. Due to the large amount of data, Western Digital sought an enterprise solution, and it wanted to build predictive models on that data. The company turned to SAS for a big data analytics solution.

Predicting failures and protecting product quality

SAS Asset Performance Analytics monitors equipment sensors and tags machine-to-machine data to identify hidden patterns that predict failures. “SAS’ comprehensive analytics software solution has provided us the ability to do complex data analysis generating new useful analytics insights for our business,” says Sim. “With a built-in case management system, the solution gives Western Digital engineers the insights they need to identify possible failures early in the production process and make timely decisions to avoid a yield excursion, ensuring Western Digital hard drives are of the highest quality.”

The engineers can perform a series of functions, including data extraction, data conversion and data analysis. All device performance indicators are monitored, so once an exception occurs with the device, the system can provide an alert to the engineers so they can make critical decisions quickly.

Western Digital’s precision in identifying a yield excursion lowered the overall number of returned units, which in turn has boosted customer loyalty and trust, having a direct bearing on the company’s revenue.

Challenge

Identify potential failures early in the production process and subsequently avoid yield excursions to ensure both volume and efficiency in the manufacturing and distribution of hard disk drives.

Solution

Benefits

Precision in identifying a yield excursion lowered the overall number of returned units, which in turn has boosted customer loyalty and trust, having a direct bearing on the company’s revenue.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.